Weak El Niño and Winter Climate in the Mid- to High Latitudes of Eurasia

PENG ZHANG

Department of Atmospheric and Oceanic Sciences & Institute of Atmospheric Sciences, Fudan University, Shanghai, and

Earth System Modeling Center, Nanjing University of Information Science and Technology, Nanjing, China

BIN WANG

Earth System Modeling Center, Nanjing University of Information Science and Technology, Nanjing, China, and Department of

Atmospheric Sciences and International Pacific Research Center, University of Hawai‘i at M�anoa, Honolulu, Hawaii

ZHIWEI WU

Department of Atmospheric and Oceanic Sciences & Institute of Atmospheric Sciences, Fudan University, Shanghai, China

(Manuscript received 28 August 2017, in final form 12 August 2018)

ABSTRACT

According to the sea surface temperature anomaly (SSTA) intensity in the Niño-3.4 region and the east–

west gradient across the Pacific, three types of El Niño are identified in this work. An event with larger than

average intensity is defined as a strong El Niño, all others are considered to be weak events. Almost all strong

El Niños are concurrent with a large gradient, which is featured by negative SSTAs in the western Pacific and

positive SSTAs in the equatorial eastern Pacific (EP) and Indian Ocean (IO). According to the east–west

gradient, the weak events can be subdivided into gradient-weak (GW) El Niño and equatorial-weak (EW) El

Niño. The GW El Niño characterizes a great east–west gradient without a significant IO SSTA. In contrast,

the EW event features a positive SSTA over the tropical IO and EP. The impact of GWEl Niño on the North

Atlantic–Eurasia continent (NA–Eurasia) displays a negative North Atlantic Oscillation (NAO)-like at-

mospheric anomaly, resulting in a drier and cooler-than-normal winter over Eurasia. Observational and

numerical evidence indicate that the prolonged subtropical jet from the North Pacific to NA acts as a

waveguide that captures the planetary Rossby waves generated by the GW El Niño. This waveguide favors

the propagation of the perturbations into the downstream regions, which would affect the NA–Eurasian

climate. However, the EWEl Niño is accompanied by a relatively weak subtropical jet that cannot impact the

NA–Eurasian climate significantly. For the strongElNiño, the absence of theNAO signal can be attributed to

the counteracting of the teleconnections triggered by the Pacific and the tropical IO.

1. Introduction

El Niño–Southern Oscillation (ENSO) is a prominent

source of climate predictability that exerts a significant

impact on global climate, which has been investigated

widely (e.g., Jin et al. 1994; Ropelewski and Halpert

1996; Trenberth and Caron 2000; Wang et al. 2008; Wu

et al. 2009; Wu and Li 2009; Wu and Lin 2012). Gener-

ally, ENSO can influence the climate over the North

Pacific (NP) and North America via the Pacific–North

America (PNA) teleconnections (Wallace and Gutzler

1981; Horel and Wallace 1981; Lin and Wu 2011) and

can modulate the Asian climate through maintaining

the western North Pacific anticyclone anomalies (Wang

et al. 2000). However, so far, its impacts on the North

Atlantic and Eurasian region (NA–Eurasia) have remained

somewhat debatable (Brönnimann 2007; Rodríguez-Fonseca et al. 2016; Polvani et al. 2017).

During the last century, the studies of Ropelewski

and Halpert (1987) and Halpert and Ropelewski (1992)

suggested that ENSO-related temperature and precipi-

tation anomalies are difficult to detect over the NA–

Eurasia region. Several influential factors have been

proposed to explain such a nonstationary relation-

ship (Brönnimann 2007), such as the variability of the

ENSO signal itself, which may result in different effects

in Europe (Greatbatch et al. 2004); tropical volcanicCorresponding author: Prof. Zhiwei Wu, zhiweiwu@fudan.

edu.cn

15 JANUARY 2019 ZHANG ET AL . 405

DOI: 10.1175/JCLI-D-17-0583.1

� 2018 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS CopyrightPolicy (www.ametsoc.org/PUBSReuseLicenses).

eruption, which is probably the most important external

forcing factor disturbing the ENSO signal (Brönnimann

et al. 2007); and some other non-ENSO-related climate

factors (Mathieu et al. 2004; Garfinkel and Hartmann

2010). However, such a claim was challenged by sub-

sequent studies (Brönnimann 2007; Ineson and Scaife

2009; Li and Lau 2012). Based on model results, Merkel

and Latif (2002) showed that the El Niño events could

significantly affect the climate anomalies over Europe—

more importantly, the anomalous patterns conform

with a negative North Atlantic Oscillation (NAO). This

finding has been proven by more recent papers (e.g.,

Ineson and Scaife 2009; Graf and Zanchettin 2012; Li

and Lau 2012), which showed that the wintertime El

Niño can excite a negative phase of anNAO-like pattern

with colder and drier-than-normal conditions prevailing

over Europe (Brönnimann et al. 2007). Some studies

further explained that when ENSO events occur, the

subtropical jet stream may be activated as a ‘‘bridge’’

that connects tropical Pacific and NAO signals (Graf

and Zanchettin 2012; Zhang et al. 2015). Other than the

roles of the troposphere, the tropical warming excites a

polarward-propagating Rossby wave train, which can

also extend upward and reach the stratosphere, resulting

in a weaker polar vortex that drives a negative NAO

anomaly over the NA–Eurasia (e.g., Perlwitz and Graf

1995; Bell et al. 2009; Ineson and Scaife 2009; Butler

et al. 2014; Domeisen et al. 2015; Polvani et al. 2017;

Richter et al. 2015; Calvo et al. 2017).

Because of the complexity of ENSO itself, the mag-

nitudes and patterns of tropical sea surface temperature

anomalies (SSTAs) vary among individual El Niño and

La Niña episodes (Capotondi et al. 2015). In particular,

the strong ENSO events (especially the so-called ‘‘super

El Niños’’ such as 1982, 1991, 1997, 2015, etc.) gave rise

to extensive damage to property, injuries, and loss of

lives. The scientific community thus has paid close at-

tention to these strong events (Schreiber and Schreiber

1984; Philander and Seigel 1985; McPhaden 1999; Wang

and Weisberg 2000; L’Heureux et al. 2017; Levine and

McPhaden 2016; Paek et al. 2017; and many others).

However, what are the possible influences of warm

ENSO events with a different intensity? Toniazzo and

Scaife (2006) found that the atmospheric anomalies

show opposite signs over eastern NA for a strong and

moderate ElNiño. Recently, Hoell et al. (2016) reported

that the precipitation in California is also susceptible to

El Niño intensity.

Moreover, according to the locations of anomalous

convective centers over the tropical Pacific, the warm

ENSO episodes can be defined as the equatorial central

Pacific (CP) or the equatorial eastern Pacific (EP) El

Niño (Larkin and Harrison 2005; Ashok et al. 2007;

Weng et al. 2007; Kao and Yu 2009; Kug et al. 2009).

Their opposites are deemed to be the CP or EP La Niña(Cai and Cowan 2009; Shinoda et al. 2011). With dif-

ferent SSTA patterns, the wintertime EP and CP El

Niño (La Niña) events exert quite different impacts on

the European climate (Graf and Zanchettin 2012;

Hurwitz et al. 2014; Zhang et al. 2015). Apart from the

shift of the maximum SSTA location, the zonal SST

anomalies gradient between the tropical western Pacific

(WP) and tropical EP is also an important feature of

ENSO (Hoell and Funk 2013). Recently, Wang et al.

(2013) proposed a new ENSO-related concept, mega-

ENSO, which is defined by using the averaged WP

K-shaped SST minus averaged EP triangle SST (Wang

et al. 2013, their Fig. 3). Thus, the mega-ENSO not only

contains the zonal SST gradient over the tropical WP

and tropical EP but also reflects the meridional gradi-

ent between the tropical and extratropical Pacific. This

new concept has garnered attention from many re-

searchers (Kim and Ha 2015; Wu and Yu 2016; Wu and

Zhang 2015; Zhang et al. 2016; Zhang et al. 2017).

While considerable efforts have been made to charac-

terize ENSO episodes through tropical Pacific SSTA

distribution, few analyses have examined the gradient

that exists during ENSO episodes nor have they tried

to classify ENSO events depending on the intensity

and gradient simultaneously. Here, another question

is raised. Does the change of the wintertime ENSO

SSTA gradient exert different impacts on the Eurasian

climate?

This study aims to investigate the different atmo-

spheric anomalies and their associated climate effects

over the NA–Eurasia region during different El Niñoevents, which are classified by the SSTA intensity in the

Niño-3.4 region and the SSTA gradient between theWP

and the EP. In this paper, section 2 introduces the data,

model, and experiment designs. The ENSO events are

first grouped based on the SSTA intensity and second

subdivided based on the SST gradient using the Niño-3.4 and mega-ENSO indices in section 3. In section 4,

we display the atmospheric responses to different

ENSO events over the NA–Eurasia region. Section 5

will discuss the possible mechanisms of how the vari-

ous categories of El Niño affect the NA–Eurasian

climate. The summary and discussion are presented in

section 6.

2. Dataset, model, and experiments design

a. Observation data and indices

In this study, the period of datasets used ranges

from September 1957 to February 2016, including the

406 JOURNAL OF CL IMATE VOLUME 32

following: 1) monthly SST data from the merged (arith-

metic mean) Extended Reconstructed SST, version 4

(ERSST.v4; Huang et al. 2015, 2016; Liu et al. 2015) and

the Hadley Centre Sea Ice and Sea Surface Tempera-

ture dataset (HadISST; Rayner et al. 2003) with hori-

zontal resolution of 28 3 28; 2) ERA-40 (Uppala et al.

2005) data for the period of September 1957–February

1979, and ERA-Interim (Dee et al. 2011) from Janu-

ary 1980 to February 2016 with horizontal resolu-

tion of 1.58 3 1.58. The climatological difference

between the ERA-40 and ERA-Interim datasets for

the period of 1980–2002 is removed from 1980–2016

ERA-Interim data to maintain temporal homoge-

neity. 3) Monthly global analysis of gauge observa-

tions [NOAA Precipitation Reconstruction (PREC);

Chen et al. 2002] on a fixed 1.08 3 1.08 longitude–latitude grid; 4) monthly mega-ENSO index (de-

fined within the region of 408N–408S, 1208E–908W)

is calculated depending on the definition of Wang

et al. (2013); 5) the ENSO events were identified

through the Niño-3.4 index (the region of 58N–58S,1208E–1708W), which is defined as the 3-month run-

ning mean of merged SSTAs in the Niño-3.4 region

based on centered 30-yr base periods (for the

method see thewebsite http://www.cpc.noaa.gov/products/

analysis_monitoring/ensostuff/ensoyears.shtml); and 6)

monthly station-based NAO index (Hurrell 1995). The

1957 winter refers to December 1957 and January–

February 1958. The deviation from the average over

the ENSO-neutral (normalized Niño-3.4 index

between 20.5 and 0.5) years was conducted as the

anomalies for all variables. Considering that the surface

temperature and precipitation data may contain an

upward trend, the data from 1957 to 2015 are detrended

to eliminate the long-term trend influence. And the

results based on the nondetrended data are nearly the

same.

b. Definition of different types of El Niño events

The traditional Niño-3.4 index can well represent

the intensity of ENSO events but cannot character-

ize the variation of the ENSO SSTA gradient over

the Pacific. The mega-ENSO index is, therefore, in-

troduced to distinguish the El Niño events with a

strong or weak gradient. Both indices are shown in

Fig. 1a and do not exhibit pronounced trends. The

trends of the Niño-3.4 and mega-ENSO indices

are 20.007 and 0.0072, respectively—not exceeding

the 90% confidence level Mann–Kendall trend sig-

nificance test (Hamed and Rao 1998; Mondal et al.

2012). On the interannual time scale, the mega-

ENSO index is highly correlated with the Niño-3.4index (the correlation coefficient is 0.9). Compared

with the Niño-3.4 index, however, the mega-ENSO

index is defined in a very different way. It is calcu-

lated by using the averaged west Pacific K-shaped

SST minus the averaged east Pacific triangle SST.

The Niño-3.4 region is included in the east Pa-

cific triangle region. The mega-ENSO, therefore, is

negative for an El Niño. And mega-ENSO shows

a spatial pattern similar to the ENSO-like inter-

decadal variability and the interdecadal Pacific Os-

cillation (IPO), containing a much broader range

than that of conventional ENSO indices.

FIG. 1. (a) Time series of the DJF Niño-3.4 and mega-ENSO index. For comparison purposes, the mega-ENSO

index is multiplied by 21. (b) Scatter map of the DJF Niño-3.4 and mega-ENSO indices for GW ENSO (red

circles), EW ENSO (green crosses), and strong ENSO (purple triangles). The red (blue) dashed line denotes 1.1

(21.1), and the black dashed line denotes 0.7 (20.7). (c) Time series of the DJF IPO and mega-ENSO index.

15 JANUARY 2019 ZHANG ET AL . 407

Figure 1c shows the normalized mega-ENSO and IPO

index; their correlation coefficient is 20.74. The IPO

index is consistent with the definition given by Dai

(2013), which is the second leading EOF of the 3-yr

moving-average global SSTs. Although the correlation

coefficient of mega-ENSO and IPO is significant, the

amplitude in the particular years is quite different.

Furthermore, the mega-ENSO contains the SST gradi-

ent of the eastern and the western Pacific, whichmay not

be reflected by IPO index. That is why the mega-ENSO

index is used in our research.

By the Niño-3.4 and mega-ENSO indices, the steps of

grouping El Niño events goes as follows: 1) if a nor-

malized DJF Niño-3.4 index is greater than 0.5, an El

Niño winter is considered to occur. The average value of

the normalized DJF Niño-3.4 index for these winters is

1.1. Therefore, a year with the normalized DJF Niño-3.4index greater than 1.1 is defined as a strong El Niño,otherwise, it is considered to be a weak El Niño. Theother values between 1 and 1.5 standardized departures

of the Niño-3.4 index can also be selected as the

threshold, which shows similar results. 2) We group the

strong (weak) El Niños depending on the gradient. For

the strong gradient El Niño cases, a prerequisite should

be satisfied: an El Niño event with a normalized mega-

ENSO index less than 20.7. For the weak gradient El

Niño, the normalized mega-ENSO index should be

more than 20.7. The value of this threshold is chosen

after the comparison of the SSTA for each El Niño year

(figure not shown). An interesting phenomenon is that

almost all strong El Niños have a significant gradient

(except 2009, the composite with or without the vari-

ables in this year does not influence qualitative results)

and only weak El Niños can be subdivided (Fig. 1b). For

convenience, the gradient-weak (GW) El Niño and

equatorial-weak (EW) El Niño in the text below refer

to the weak events with strong and weak gradients. All

events are listed in Table 1 as well as the different kinds

of La Niña episodes. However, the sample size of

GW (EW) La Niñas is too small to obtain a convincing

result. That is why, in this manuscript, we mainly pay

attention to the warm ENSO events. In Table 1, the CP

El Niño years are marked with bold fonts according to

the previous studies (e.g., Ashok et al. 2007; Graf and

Zanchettin 2012). The CP El Niño seems to be mere

random chance among the three types of newly defined

El Niño in this study.

We acknowledge that the research samples for three

types of El Niño events are quite limited and very likely

to be influenced by the large internal variability of the

atmosphere, which has a large impact on the ENSO

teleconnections (Deser et al. 2017). We perform nu-

merical experiments to investigate the role of SSTAs

associated with different types of El Niños in the at-

mospheric anomalies over the North Atlantic.

c. Simulations

All numerical experiments were performed using an

AGCM, the fifth-generation European Centre–Max

Plank Institute model (ECHAM5.4; Roeckner et al.

2003). We used the T63L19 version, which features a

horizontal resolution of 1.8758 and 19 vertical levels. TheSST forcing fields were derived from the Atmospheric

Model Intercomparison Project (AMIP) II SST and sea

ice concentration boundary conditions. In the control

run (CTRL), AMIP II historical SST was prescribed for

20 sample years: 1958, 1960, 1961, 1966, 1967, 1969, 1974,

1977, 1979, 1980, 1981, 1985, 1987, 1990, 1996, 2000,

2001, 2003, 2004, and 2006. Almost all of them are weak

or neutral ENSO andNAO years (the normalized Niño-3.4 and NAO indices are between 20.7 and 0.7).

Therefore, the impact of ENSO and NAO signals could

be reduced. The simulations for each sample were in-

tegrated for 38 months. Taking 1961 as an example, the

simulations were performed for the period from

1 January 1958 to 28 February 1961, the SSTs that

matched the 1958–61 time periods. Spinup spans the

first 35 months and the last 3-month-average was taken

as a sample. To contrast the different climate impacts of

the SSTA modes related to the disparate El Niños, weperformed a set of sensitivity experiments (see Table 2)

with their initial conditions taken from the control

experiment. Next, the observational composite SSTA

added to the control experiments was prescribed for

each sample. At last, 20 ensemble members for each

control and sensitivity experiment were considered to

reduce the influence of the initial conditions and the

internal variability. For the first sensitivity experiment

(GW El Niño warming, GW_EN), the composite SST

anomaly over the Pacific (408S–408N, 1208E–708W,

anomalies are set to zero in the outside region) during

TABLE 1. ENSO event classification using the Niño-3.4 andmega-

ENSO index. CP El Niño years are set in bold font. El Niño years

with sudden stratospheric warmings (SSWs) are set in italic font.

Events Years

Strong ENSO El Niño 1957, 1965, 1972, 1982, 1991,

1997, 2009, 2015 (8)

La Niña 1970, 1973, 1975, 1988, 1998,

1999, 2007, 2010 (8)

Weak ENSO GW El Niño 1958, 1968, 1976, 1977, 1979,

1986 (6)

GW La Niña 1971, 1974, 2000, 2008, 2011 (5)

EW El Niño 1963, 1969, 1987, 1994, 2002,

2004, 2006, 2014 (8)

EW La Niña 1967, 1983, 1984, 1995, 2005 (5)

408 JOURNAL OF CL IMATE VOLUME 32

the GW El Niño winter is added to the control exper-

iments from December to February. To enhance the

atmospheric response, we used the SST difference

between warm and cold GW ENSO. The prescribed

SSTA is similar to the SSTA distributions for GW El

Niño (Fig. 2b) but has a larger amplitude. For the second

sensitivity experiment (EWElNiñowarming, EW_EN),

the tropical Pacific SSTA (208S–208N, 1608E–708W)

during the EW El Niño winter (EW El Niño minus EW

La Niña) is imposed. Since the positive SSTA appears

significantly in the Indian Ocean (IO) during the EW El

Niño winter, the third experiment (EW_EN_IO) is de-

signed the same way as the EW_EN experiment. How-

ever the positive SST anomaly for the EW El Niño is

imposed on the IO and Pacific (208S–208N, 408E–708W)

to inspect their combined contribution. For the strong

El Niño, another set of experiments is designed. In

the fourth experiment (strong El Niño, STRG_EN),

we conduct sensitivity simulations where the EP SST

warming and WP cooling forcings are both imposed to

examine the impact of the strong El Niño. During the

strong El Niño, the intensity of the SSTA is much

greater than that during the weak El Niño. The SSTA,

calculated from strong El Niño minus neutral, is large

enough to obtain a clear response in the model. We also

study possible contributions of the strong El Niño–related positive SSTA in the tropical IO (208S–208N,

408–1108E) in the fifth experiment (Indian warming,

TABLE 2. List of SST perturbation experiments conducted in

this study.

Experiments Description of SST perturbation

GW_EN SSTA associated with GWEl Niño events

imposed in the Pacific (408S–408N,

1208E–708W)

EW_EN SSTA associated with EW El Niño events

imposed in the tropical Pacific

(208S–208N, 1608E–708W)

EW_EN_IO SSTA associated with EW El Niño events

imposed in the tropical Pacific and

Indian Ocean (208S–208N, 408E–708W)

STRG_EN SSTA associated with strong El Niñoevents imposed in the Pacific

(408S–408N, 1208E–708W)

IO_WARM SSTA associated with EW El Niño events

imposed in the tropical Indian Ocean

(208S–208N, 408–1108E)STRG_EN_IO STRG_EN and IO_WARM forcings are

imposed together

FIG. 2. DJF sea surface temperature (SST; K) composite differences of (a) strong El Niño2 neutral, (b) GW El

Niño2 neutral, and (c) EWEl Niño2 neutral. Neutral refers to a year in which the Niño-3.4 index is greater than20.5 and less than 0.5. (d),(e),(f) As in (a), (b) and (c), but for precipitation (mmday21). The black dots in each

panel represent the region with anomalies significant at the 90% confidence level (Student’s t test). The purple lines

in (a) and (b) outline the eastern Pacific triangle andwestern PacificK-shaped regions where themega-ENSO index

is defined. Shading intervals are 0.2K and 0.4mmday21.

15 JANUARY 2019 ZHANG ET AL . 409

IO_WARM), as the significant warming SSTAs occur

there. In the last experiment (strong El Niño and Indian

warming, STRG_EN_IO), we inspected the possible at-

mospheric response to the combination of IO_WARM

and STRG_EN forcings.

3. Comparison of three types of El Niño

The observed large-scale SSTA and tropical pre-

cipitation patterns associated with the strong, GW, and

EW El Niños are compared in Fig. 2. During a boreal

strong El Niño winter, the SSTA shows a ‘‘seesaw’’

mode that highly resembles the mega-ENSO SSTA

pattern (purple box in Fig. 2a) with a significant negative

anomaly covering the tropical–extratropical WP and a

positive SSTA covering the tropical EP. The tropical IO

meanwhile shows a significant warming SSTA (Fig. 2a).

For the weak El Niño events, two different SSTA patterns

are presented: the GW and EW El Niños. In general, the

two kinds of weak events have similar SSTA intensity—

both are weaker than that during the strong El Niño win-

ter. Specifically, theGWElNiño displays roughly the same

pattern in the Pacific as what the strong El Niño shows

(purple box in Fig. 2b), but no significant positive SSTA

appears in the IO. Conversely, the spatial pattern of the

EW El Niño features a highly significant zonal banded

warming throughout the tropical oceans from 208N to

208S without a significant K-shaped SST cooling in the

WP and subtropical Pacific (Fig. 2c).

As expected, the tropical precipitation anomalies re-

lated to the three kinds of El Niño are distinct on ac-

count of the different SSTA distributions (Figs. 2d–f).

For the strong El Niño (Fig. 2d), significant positive

rainfall anomalies locatedmainly over the equatorial CP

and EP are accompanied by a relatively dry condition

covering theMaritimeContinent. This precipitationpattern

is in accordance with the result showed by Dai and Wigley

(2000, their Fig. 2c). For the weak El Niños, the intensity oftropical Pacific precipitation centers becomes appreciably

weaker. During the GW El Niño winter, positive pre-

cipitation anomalies straddle the date line with a westward-

shifted center and a stronger intensity than that during the

EWEl Niño winter (Figs. 2e and 2f). Another difference

in the precipitation anomaly is that a larger significant

negative anomaly appears over the Philippine Sea for

the GW El Niño but is not obvious for the EW El Niño.It is interesting to notice that the equatorial CP and EP

SSTAs intensity for the GW and EW El Niños (Figs. 2band 2c) are almost the same. But why does the GW El

Niño excite a relatively stronger precipitation anomaly

than the EW El Niño?Rearrangement of convection centers of the Walker cir-

culation during ENSO events induces large precipitation

anomalies in the tropics (Dai andWigley 2000). Thus, to

answer the aforementioned question, it is necessary to

check the variations of the Walker cell over the equa-

torial Pacific associated with the GW and EW El Niños.Figure 3 presents the composite maps of the velocity

potential and the divergence wind at 850 hPa with re-

spect to the GW and EWEl Niños. For the weak events,

the vertical movements over the tropical Pacific exhibit

an east–west dipolemode. Sinkingmotion centered over

the Maritime Continent and tropical WP features a

strong divergence, and the contrary behavior can be

detected over the tropical EP. Nevertheless, the con-

vergence over the tropical EP and the divergence over

the WP in response to the GW El Niño (Fig. 3a) are

stronger than that to the EWEl Niño (Fig. 3b). As such,

the SSTA for the GW El Niño displays a stronger east–

west gradient that can induce a stronger atmospheric

response than that for the EW El Niño.

4. Atmospheric responses over Eurasia

The different ENSO SST anomaly patterns may

give rise to large discrepancies in the extratropical

atmospheric circulation as well as regional climate

directly by exciting the ENSO teleconnection (Horel

and Wallace 1981; Wang et al. 2000; many others) or

indirectly through the ‘‘atmospheric bridge’’ (Lau andNath

1996; Alexander et al. 2002; Graf and Zanchettin 2012). In

the present paper, we pay more attention to how the three

FIG. 3. DJF composite maps of the velocity potential (contour)

and the divergence wind (vector) at 850 hPa. (a) GW El Niño 2neutral and (b) EW El Niño2 neutral. The shadings in each panel

represent the region with anomalies significant at the 90% confi-

dence level (Student’s t test).

410 JOURNAL OF CL IMATE VOLUME 32

kinds of El Niño affect the climate of the Eurasian conti-

nent and the mechanism behind them.

Figure 4 compares the large-scale horizontal wind

and geopotential height anomalies at 1000hPa (Z1000,

UV1000) for the three kinds of El Niño. As one of the

most prominent ENSO teleconnections, the Aleutian

low (AL) tends to build up and shifts southeastward

during El Niño (Bjerknes 1966, 1969). For the strong

events, the AL becomes deeper than that for the weak

events, and a PNA-like teleconnection is excited by the

strong tropical warming SSTA (Fig. 4a). For the weak El

Niños (Figs. 4b,c), compared to the EW El Niño com-

posite, the significant negative Z1000 anomaly over the

Aleutian area mildly shifts southeastward during the

GW El Niño. However, pronounced discrepancies at

Z1000 can be observed over theNA–Eurasia sector. The

Z1000 anomaly during the GW El Niño winter shows a

negative NAO-like structure (Fig. 5a) with an obvious

reinforced anomalous Iceland low and Azores Islands

high (Fig. 4b). Nevertheless, the NAO-like pattern dis-

appears during the EW El Niño winter (Fig. 4c). The

scatterplot in Fig. 5b displays the relationship between

NAO and the three types of El Niño. Five out of six GW

warm ENSO episodes occur accompanied by the nega-

tive NAO-like patterns, and the exception corresponds

to an NAO-neutral pattern (NAO index 5 20.05).

However, for the strong and EW El Niños, the possi-

bility of the occurrence of a positive or negative NAO-

like anomaly is fifty-fifty. This phenomenon indicates

that compared to the EW and strong events, the connec-

tion of GW El Niño and NAO signals seems more stable.

When an El Niño event occurs concurrently with

NAO, their combined effect can lead to even greater

or different influences than each of them does alone

(Seager et al. 2010; Wu and Lin 2012; Wu and Zhang

2015).Many other works have proven that during winter

the NAO signal contributes profoundly to precipitation

and surface temperature in NA–Eurasia (Jones et al.

2003; Graf and Zanchettin 2012; Zhang et al. 2015).

Figure 6 examines the mean winter (DJF) 2-m air tem-

perature (T2m) and precipitation anomalies of three

kinds of El Niño over Eurasia. Great T2m and pre-

cipitation differences are found in this region. During

the strong El Niño winter, there are no significant T2m

anomalies over Eurasia except for central Europe

(Fig. 6a). The precipitation anomalies display a mono-

center pattern with the significant region mainly located

to the northeast of the Caspian Sea (Fig. 6d). During the

GW El Niño winter, midlatitude responses show nega-

tive T2m anomalies over eastern Europe and northern

Asia—up to 22.2K colder than normal (Fig. 6b). Dur-

ing the EW El Niño winter, no significant T2m anoma-

lies emerge in Eurasia (Fig. 6c). Precipitation-wise, a

significant south–north dipole mode is detected dur-

ing the GW El Niño winter with significant dry con-

ditions controlling northern Eurasia and relatively

wet conditions covering southern Eurasia (Fig. 6e).

However, for the EW El Niño, there is only a small

significant negative anomaly to the south of Lake

Baikal (Fig. 6f).

All these phenomena imply that the T2m and pre-

cipitation anomalies respond rather differently to the

three types of El Niño during the past 59 winters.

Among them, the response to GW events is the most

significant. Combined with Fig. 4b, the spatial pattern

displayed in Figs. 6b and 6e can be explained to some

extent. When a GW El Niño event—accompanied by a

negative phase of NAO—occurs in the wintertime, the

reduced cross-NA westerly flow restricts the warm and

moist air blowing from the ocean but favors cold and

dry air coming down from the Arctic. This circulation

pattern prevails over much of the Eurasian continent,

resulting in a colder and drier-than-normal condition

FIG. 4. DJF 1000-hPa geopotential height (Z1000; 10m)

and wind (UV1000; m s21) composite differences of (a) strong

El Niño 2 neutral, (b) GW El Niño 2 neutral, and (c) EW El

Niño 2 neutral. The vectors and shadings in each panel represent

the region with anomalies significant at the 90% confidence level

(Student’s t test). The contour interval is 10m.

15 JANUARY 2019 ZHANG ET AL . 411

there—in accordance with the demonstration of Hurrell

et al. (2003) and Jones et al. (2003). Over southern

Eurasia, the positive precipitation anomalies may

be induced by the anomalous southerly flow trans-

porting warm and wet air from tropical Africa and the

Arabian Sea. And such a pathway through which El

Niño impacts the precipitation in southwest central

Asia has been discussed by Mariotti (2007). However,

during the strong and EW El Niño winters, tropical

SSTA cannot exert a significant impact on Eurasia.

FIG. 5. (a) The regression maps of the Z1000 (10m) onto the NAO index for 1957–2015. The shadings indicate

that the correlations are significant at the 90% confidence levels (Student’s t test). The contour interval is 10m.

(b) Scatter map of the DJF NAO and Niño-3.4 indices for GW El Niño (red circles), EW El Niño (green crosses),

and strong El Niño (purple triangles). The blue dashed line denotes 1.1.

FIG. 6. As in Fig. 2, but for 2-m air temperature (T2m; K) and precipitation (mmday21) over Eurasia.

412 JOURNAL OF CL IMATE VOLUME 32

For what reasons did the GWEl Niño connect with the

NAO signal?

It is known that jet streams can affect the propagation

of the tropical-induced planetary waves and lead to

atmospheric anomalies depending on 1) a strong jet stream

acting as a zonal waveguide, 2) the strength of Rossby

waves, and 3) thewaves that cross the jet streams (Ambrizzi

and Hoskins 1997). For an ENSO event, a Rossby wave

can be generated by enhanced precipitation and related

latent heat released at the equator that propagates from

low-latitude regions to the Arctic. When the poleward-

propagating Rossby wave crosses the subtropical jet

stream, it can be trapped and then the disturbance will

propagate downstream along the jet stream waveguide—

therefore impacting the downstream region. Graf and

Zanchettin (2012) demonstrated that the subtropical

jet, as an atmospheric bridge, is of great significance in

linking the NAO signal and tropical Pacific warming.

Using observational data and numerical simulation,

Zhang et al. (2015) verified that the atmospheric bridge

also works during the La Niña winter. However, it is still

unclear why the GW El Niño connects with the NAO.

Whether the subtropical jet can bridge the GW El Niñoand NAO teleconnection calls for further investigation.

In response, we give the composite 200-hPa zonal wind

(U200) anomalies to explore the variations of El Niño–related jet streams (Fig. 7).

From the composite maps, the U200 anomalies—

related to the three kinds of El Niño—exhibit a tripolar

structure over NP (Fig. 7). In the subtropical NP, sig-

nificant positive anomalies indicate that the East Asia

subtropical jet is strengthened. For the GW El Niño(Fig. 7b), the strengthened anomalous East Asia sub-

tropical jet elongates far eastward from the EP to NA–

Eurasia. Significant negative anomalies extend zonally

from the extratropical NP to NA, indicating a weakened

Atlantic jet. Accompanied by the variations of these

two jet streams, a negative NAO-like pattern appears

over the NA–Eurasia sector (Fig. 4b). Compared to

GWEl Niño, the elongations of the two jet streams are

not appreciable during the strong El Niño winter.

Meanwhile, the cores of two anomalous jet streams

over the North American and Atlantic sectors are

displaced westward (Fig. 7a). This anomalous U200

pattern resembles that of Graf and Zanchettin (2012,

their Fig. 4, middle). For the EWEl Niño (Fig. 7c), the

upper troposphere subtropical westerly winds become

much weaker at the eastern tip of the subtropical jet

stream. It suggests that different kinds of El Niño will

excite different responses in the East Asian sub-

tropical and Atlantic jets, accompanied by the various

atmospheric responses over the NA–Eurasia region

(Figs. 4 and 6).

According to the analysis above, we may speculate

that El Niño–related jet streams are the key factors to

modulating the connection of El Niño and NAO. But

the composites do not guarantee any cause and effect.

For example, it is hard to tell whether the different re-

sponses of the jet streams are caused by the switch of the

El Niño types or vice versa. Some researchers have

pointed out that the ENSO-related extratropical Pacific

SSTAs are excited by the atmosphere, not the opposite

way around (Lau and Nath 1990; Alexander et al. 2004).

Nevertheless, Robinson (2000) argued that the response

of the extratropical atmosphere to underlying SSTAs

is weak but not ignorable. Thus, more evidences are

needed to confirm causality.

5. Physical mechanisms

Based on the observed analyses above, the different

SSTA patterns for the two kinds of weak El Niño are

possibly accountable for the two kinds of atmospheric

anomalies over NA–Eurasia. To verify the specific

FIG. 7. As in Fig. 2, but for zonal wind (m s21) at 200 hPa (U200).

The contour interval is 1 m s21.

15 JANUARY 2019 ZHANG ET AL . 413

processes, a set of experiments was performed—as de-

scribed in section 2. Figure 8 shows the imposed SSTA

for each sensitivity experiment. First, we checked the

tropical precipitation response to the GW_EN, EW_

EN, and EW_EN_IO forcings relative to the CTRL

experiment (Fig. 9). In accordance with the observa-

tional results, the imposed EP SST warming, WP and

extratropical Pacific cooling in the GW_EN simulation

(Fig. 9a) result in stronger tropical Pacific precipitation

anomalies than that of the EW_EN and EW_EN_IO

simulations (Figs. 9b and 9c). Figure 10 displays the re-

sponses of SLP anomalies. The GW_EN SSTA forcing

induces a strengthened AL over the NP and a negative

NAO-like SLP anomaly over the NA (Fig. 10a). This

anomaly pattern markedly resembles the observed GW

El Niño composition (Fig. 4b). Under the EW_EN

forcing, the anomalous AL is still strong. However, over

the NA, the NAO-like atmospheric response disappears

(Fig. 10b). Comparing these two simulations, the most

obvious difference is that the NAO-like SLP anomaly

does not appear in response to the equatorial EP

warming without the cooling in the WP K-shaped re-

gion. Next, the EW_EN_IO experiment was performed.

Considering that an EW El Niño is often observed to

occur with an IO SST warming (Fig. 2c), we added a

positive IO SSTA to the EW_EN forcing. The result

shows a slightly northwestward-shifted AL (Fig. 10c)

compared with the GW_EN simulation (Fig. 10a).

Meanwhile, the NAO-like atmospheric response is not

significant over NA–Eurasia (Fig. 10c)—the outcome

basically reproduced the observational result (Fig. 4c).

Above all, different SSTA patterns for the two kinds of

weak events can result in roughly similar atmospheric

responses over the NP. Yet, they trigger quite different

responses over the NA.

We speculated above that the GW El Niño is linked

to NAO through the subtropical jet stream. Thus, it is

necessary to check the jet streams excited by the several

kinds of SSTA forcings in the model. The results are

shown in Fig. 11. Forced by the GW El Niño SSTA

(Fig. 11a), the responses of the jet streams also exhibit a

tripolar structure over the NP. Accompanied by a neg-

ative NAO-like SLP anomaly over the NA–Eurasia

region, a strengthening East Asia subtropical jet and a

weakening Atlantic jet extends zonally from the NP to

NA–Eurasia. For the EW_EN and EW_EN_IO simu-

lations (Figs. 11b and 11c), the jet streams are un-

surprisingly strengthened (weakened) mainly over the

NP. Such anomaly patterns are well consistent with the

observations (Figs. 7b and 7c). According to the obser-

vational and numerical evidence, the mechanism of

whether the weak El Niño can link to NAO or not,

therefore, can be concluded as follows. During the GW

El Niño winter, when the tropical EP warming and the

equatorial WP cooling SSTAs are coupled with each

other (Fig. 2b), the tropical Pacific precipitation anom-

alies will be stronger than during the EW El Niño(Figs. 2e and 9a). Also, the anomalousAL in response to

FIG. 8. (a)–(f) The SSTA forcing regions mentioned in Table 2.

414 JOURNAL OF CL IMATE VOLUME 32

the GW El Niño SSTA is located relatively farther east

than that of the EW El Niño (Figs. 4b and 10a). Mean-

while, strong abnormal convective heating over tropical

oceans excites the subtropical jet elongating zonally

from NP to NA–Eurasia. Such circumstances probably

enhance the possibility of the planetary Rossby waves,

which may be trapped by the subtropical jet stream

during their poleward propagation. Along the sub-

tropical jet stream waveguide, some of the perturbation

responses will propagate zonally eastward from Pacific

sector to the downstream regions and contribute to the

weakening of the Azores high and to the negative phase

of NAO (Figs. 7b and 11a). The eastward elongated

subtropical jet stream cannot be triggered during EWEl

Niño (Figs. 7c and 11c) when relatively weaker abnor-

mal convective heating occurs near the date line (Figs. 2f

and 9c). Under these conditions, the EW El Niñoanomaly cannot link with the NAO signal (Figs. 4c

and 10c).

Differing from the weak events, the strong El Niñoevents—especially the so-called super El Niños—have

gained wide attention for their significant climate im-

pacts (Wolter and Timlin 1998; Chavez et al. 1999; Lau

and Weng 2001; Wu et al. 2010; Christiansen et al. 2016;

and so on). From the observations, the strong El Niños

are featured by a strong east–west Pacific SSTA gradient

and significant IO SST warming (Fig. 2a). We have

proven that the GW_EN forcing (with strong east–west

SSTA gradient but weaker amplitude in the tropical

Pacific than that of STRG_EN forcing) is related

to the negative NAO. In previous studies, Hoerling

et al. (2004) and Bader and Latif (2005) had proven

that imposing a positive SSTA on the tropical IO can

induce a positive NAO anomaly. Naturally, we specu-

late here that the absence of the NAO signal during

strong El Niño winter may attribute to the counter-

acting of the teleconnections excited by the two oceans.

Therefore, another set of experiments was performed to

examine the possible effects of the different oceans on

the NA atmospheric circulation. Figure 12a shows the

SLP responses in the STRG_EN simulations relative to

the control run. Resembling the GW_EN simulation,

the STRG_EN forcing can excite a negative phase of

NAO-like SLP anomaly—implying that the linking of El

FIG. 9. (a) Tropical precipitation responses in the ECHAM5

regarding a difference between GW_EN forcing and the control

run. (b),(c)As in (a), but for EW_ENandEW_EN_IO forcing. The

dots in each panel represent the region with anomalies significant

at the 90% confidence level (Student’s t test). The contour interval

is 2mmday21.

FIG. 10. (a) DJF sea level pressure (SLP) responses in the

ECHAM5 regarding a difference betweenGW_EN forcing and the

control run. (b),(c) As in (a), but for EW_EN and EW_EN_IO

forcing. The shadings in each panel represent the region with

anomalies significant at the 90% confidence level (Student’s t test).

The contour interval is 1 hPa.

15 JANUARY 2019 ZHANG ET AL . 415

Niño and NAO possibly depends on the east–west gra-

dient rather than the amplitude of the tropical Pacific

SSTA. Furthermore, we conducted another experiment

(IO_WARM), in which the SSTA forcing was only

imposed on the tropical IO. In agreement with the pre-

vious researches (Hoerling et al. 2004; Bader and Latif

2005), a positive phase of NAO-like response appears

over the NA–Eurasia region accompanied by a weak-

ened AL (Fig. 12b). At last, the STRG_EN_IO simu-

lation was conducted, in which the STRG_EN and

IO_WARM forcings were both added. The result is

displayed in Fig. 12c. Under the STRG_EN_IO forcing,

the NAO-like SLP anomaly disappears despite the fact

that AL is still strong. The atmospheric responses re-

semble that of the EW_EN_IO forcing (Fig. 10c). Bader

and Latif (2005, hereafter BL05) have revealed that the

precipitation response especially near the south equa-

torial Indian Ocean is characterized by an increase in

rainfall due to higher IO SSTs. The mean DJF 300-hPa

meridional wind response for the positive IO SSTA

forcing resembles the circumglobal pattern, resulting

in a positive phase of NAO. Our IO experiment results

(not shown) are consistent with what BL05 analyzed.

When IO warming induces a positive phase of the NAO

and a stronger gradient El Niño induces a negative

phase of the NAO, their combined effect might coun-

teract the eastward extension of the subtropical jet over

the North Atlantic. It should be noted that in compari-

son with the observations (Fig. 4a), the SLP responses

overNorthAmerica triggered by theEW_EN_IO forcing

are not obvious.

The numerical simulations listed above indicate that

the three kinds of warm ENSO episodes exert distinct

impacts on the NA–Eurasia atmosphere. The subtropi-

cal jet stream serves as an atmospheric bridge and is

considered to be one of the key factors in linking the

tropical Pacific and the NAO signals during the GW El

Niño winter. However, are there any other mechanisms

working behind the connection of ENSO and NAO?

We have already introduced the stratospheric pathway

in linking ENSO and NAO signals in the introduction.

The El Niño years with sudden stratospheric warmings

(SSWs) are italicized in Table 1 according to the study of

Butler et al. (2014) (their Table 1) and Charlton and

Polvani (2007). Only half the strong, GW, and EW El

Niño years have SSWs. Using ERA reanalysis data, the

composite maps of polar cap heights at 50 hPa are also

FIG. 12. As in Fig. 10, but for STRG_EN, IO_WARM, and

STRG_EN_IO forcing.

FIG. 11. As inFig. 10, but for zonalwind at 200hPa (U200). The dots

in eachpanel represent the regionwith anomalies significant at the 90%

confidence level (Student’s t test). The shading interval is 1m s21.

416 JOURNAL OF CL IMATE VOLUME 32

displayed to check how the stratosphere is changing in

each of El Niño categories (Fig. 13). During strong and

EW El Niño winters (Figs. 13a and 13c), neutral or in-

significant weak vortices are detected over the polar

region. Although the polar vortex became strong for

the GW El Niño, the atmospheric anomaly is still

insignificant (Fig. 13b). Therefore, compared with the

subtropical bridge, stratospheric teleconnection may

play a secondary role in the connection of GW El Niñoand NAO signals during DJF.

6. Conclusions and discussion

By using Niño-3.4 and mega-ENSO indices, the El

Niño events are classified into three types based on the

SSTA intensity and gradient (i.e., strong, GW, and EW

El Niño). An El Niño with higher-than-average SST

intensity in the Niño-3.4 region is defined as a strong

event, which features a positive SSTA in the equatorial

EP and tropical IO and a negative SSTA in the WP

K-shaped region. The strong El Niño events, however,

cannot be subdivided depending on the gradient. In

contrast, the events with lower-than-average ampli-

tude are defined as a weak El Niño, which is able to be

subdivided by the east–west Pacific SSTA gradient.

The strong gradient events are referred to as the GW

El Niño, which shows an SSTA pattern resembling

the strong El Niño without the significant tropical IO

SST warming. The weak gradient events are referred

to as the EW El Niño, which features a significant

zonal banded warming throughout the tropical oceans

without a significant negative K-shaped SSTA. These

FIG. 13. DJF 50-hPa geopotential height (Z50; 10m) composite differences of (a) strong El Niño 2 neutral,

(b) GW El Niño 2 neutral, and (c) EW El Niño 2 neutral. The dots in each panel represent the region with

anomalies significant at the 90% confidence level (Student’s t test).

15 JANUARY 2019 ZHANG ET AL . 417

differences in the amplitude and gradient of SSTA in-

dicate the probability of different fundamental dynam-

ics and climate impacts.

Although the different kinds of weak El Niñocan generate a roughly similar atmospheric response

over the extratropical NP, markedly different tele-

connections are observed over the NA–Eurasia region.

During the GW El Niño winter, when EP triangle SST

warming is coupled with western K-shaped cooling,

a negative NAO-like pattern appears over the NA–

Eurasia region accompanied by a weakened Atlantic

jet and a strengthened East Asia subtropical jet. This

weakened Atlantic jet tends to restrict the moist and

warm air from being transported from the Atlantic to

the north of Eurasia and induces a much drier and

cooler-than-normal winter condition there. However,

the NAO-like atmospheric anomaly disappears during

the strong and EW El Niño winters along with a neutral

Atlantic jet and a relatively weak East Asia subtropical

jet. No T2m and precipitation anomalies are detected in

Eurasia. Observational and numerical analyses proved

that the subtropical jet stream might be a crucial factor

in linking the El Niño and NAO signals. The positive

mega-ENSO-like SSTA could trigger the East Asia

subtropical jet elongating far eastward from NP to

NA–Eurasia. This probably enhances the possibility of

El Niño–related planetary Rossby waves propagating

along the subtropical jet stream waveguides and then

affects the downstream regions. During the GWElNiñowinter, this is the main pathway to connect ENSO with

NAO signals.Moreover, the linkage of ENSOandNAO

could also be modulated by the tropical IO. During the

strong El Niño winter, the amplitude of SSTA in the

Pacific is strong, meanwhile, a positive SSTA is also

detected on the tropical IO. For one thing, positive

mega-ENSO-like SSTA induces a negative phase of

the NAO-like anomaly. For another, previous studies

(Hoerling et al. 2004; Bader and Latif 2005) and our

numerical results have proved that tropical IO warming

may lead to a positive NAO-like atmospheric anomaly.

Thus, the combined effect of the Indian and the Pacific

Ocean results in an NAO-neutral response over the

North Atlantic. For the EW El Niño, the weak sub-

tropical jet stream makes the linkage seem less likely.

To summarize, the different kinds of El Niño would

exert different impacts on global climate in the

winter time. Through coupling with atmospheric tele-

connections, the GW El Niño can exert its influence on

the NA–Eurasia regions. But such impacts to the re-

mote areas cannot be detected during the strong and

EW El Niño winters. The climatic impacts of the weak

El Niño events, therefore, cannot be neglected. Wang

et al. (2013) believed that the mega-ENSO is one of

the primary sources of the interdecadal variations of the

North Hemisphere summer monsoon. Referencing the

methods in this study, can the ENSO events in the sum-

mertime also be subdivided? Also, what are the mecha-

nisms behind the production of the GWEl Niño and EW

El Niño? All these questions call for further research.

Acknowledgments. This work is jointly supported by

theNational Natural Science Foundation of China (NSFC)

(Grant 41790475), the National Key Research and Devel-

opment Program of China (Grant 2016YFA0601801), the

Ministry of Science and Technology of China (Grants

2015CB953904 and 2015CB453201), and the NSFC

(Grants 91637312, 41575075, 91437216, 61702275, and

41775008). Bin Wang acknowledges support from the Na-

tional Research Foundation (NRF) of Korea through a

Global Research Laboratory (GRL) grant of the Korean

Ministry of Education, Science and Technology (MEST,

2011-0021927) and the support from the Atmosphere–

Ocean Research Center at the University of Hawaii par-

tially supported by Nanjing University of Information

Science and Technology. We thank Dr. Zhiqing Xu and

three reviewers for their helpful comments.

REFERENCES

Alexander, M. A., I. Bladé, M. Newman, J. R. Lanzante, N. C. Lau,

and J. D. Scott, 2002: The atmospheric bridge: The influence

of ENSO teleconnections on air–sea interaction over the

global oceans. J. Climate, 15, 2205–2231, https://doi.org/10.1175/

1520-0442(2002)015,2205:TABTIO.2.0.CO;2.

——, N. C. Lau, and J. D. Scott, 2004: Broadening the atmo-

spheric bridge paradigm: ENSO teleconnections to the

tropical West Pacific–Indian Oceans over the seasonal cy-

cle and to the North Pacific in summer. Earth’s Climate: The

Ocean–Atmosphere Interaction,Geophys. Monogr., Vol. 147,

Amer. Geophys. Union, 85–104, https://doi.org/10.1029/

147GM05.

Ambrizzi, T., and B. J. Hoskins, 1997: Stationary Rossby-wave

propagation in a baroclinic atmosphere.Quart. J. Roy.Meteor.

Soc., 123, 919–928, https://doi.org/10.1002/qj.49712354007.Ashok, K., S. Behera, A. S. Rao, H. Y. Weng, and T. Yamagata,

2007: El Niño Modoki and its possible teleconnection.

J. Geophys. Res., 112, C11007, https://doi.org/10.1029/

2006JC003798.

Bader, J., and M. Latif, 2005: North Atlantic Oscillation response

to anomalous Indian Ocean SST in a coupled GCM.

J. Climate, 18, 5382–5389, https://doi.org/10.1175/JCLI3577.1.Bell, C. J., L. J. Gray, A. J. Charlton-Perez, M. M. Joshi, and A. A.

Scaife, 2009: Stratospheric communication of El Niño tele-

connections to European winter. J. Climate, 22, 4083–4096,

https://doi.org/10.1175/2009JCLI2717.1.

Bjerknes, J., 1966: A possible response of the atmospheric Hadley

circulation to equatorial anomalies of ocean temperature.

Tellus, 18, 820–829, https://doi.org/10.3402/tellusa.v18i4.9712.——, 1969: Atmospheric teleconnections from the equatorial

Pacific. Mon. Wea. Rev., 97, 163–172, https://doi.org/10.1175/

1520-0493(1969)097,0163:ATFTEP.2.3.CO;2.

418 JOURNAL OF CL IMATE VOLUME 32

Brönnimann, S., 2007: Impact of El Niño–Southern Oscillation on

European climate.Rev. Geophys., 45, RG3003, https://doi.org/

10.1029/2006RG000199.

——, T. Ewen, T. Griesser, andR. Jenne, 2007:Multidecadal signal

of solar variability in the upper troposphere during the 20th

century. Space Sci. Rev., 125, 305–315, https://doi.org/10.1007/

s11214-006-9065-2.

Butler, A. H., L. M. Polvani, and C. Deser, 2014: Separat-

ing the stratospheric and tropospheric pathways of El

Niño–Southern Oscillation teleconnections. Environ. Res.

Lett., 9, 024014, https://doi.org/10.1088/1748-9326/9/2/

024014.

Cai, W., and T. Cowan, 2009: La Niña Modoki impacts Australia

autumn rainfall variability. Geophys. Res. Lett., 36, L12805,

https://doi.org/10.1029/2009GL037885.

Calvo, N., and Coauthors, 2017: Northern Hemisphere strato-

spheric pathway of different El Niño flavors in stratosphere-

resolving CMIP5 models. J. Climate, 30, 4351–4371, https://

doi.org/10.1175/JCLI-D-16-0132.1.

Capotondi, A., and Coauthors, 2015: Understanding ENSO di-

versity. Bull. Amer. Meteor. Soc., 96, 921–938, https://doi.org/

10.1175/BAMS-D-13-00117.1.

Charlton, A. J., and L. M. Polvani, 2007: A new look at strato-

spheric sudden warmings. Part I: Climatology and modeling

benchmarks. J. Climate, 20, 449–469, https://doi.org/10.1175/

JCLI3996.1.

Chavez, F. P., P. G. Strutton, G. E. Friederich, R. A. Feely, G. C.

Feldman, D. G. Foley, and M. J. McPhaden, 1999: Biological

and chemical response of the equatorial Pacific Ocean to the

1997–98 El Niño. Science, 286, 2126–2131, https://doi.org/

10.1126/science.286.5447.2126.

Chen, M., P. Xie, J. Janowiak, and P. A. Arkin, 2002: Global

land precipitation: A 50-yr analysis based on gauge ob-

servations. J. Hydrometeor., 3, 249–266, https://doi.org/

10.1175/1525-7541(2002)003,0249:GLPAYM.2.0.CO;2.

Christiansen, B., S. Yang, andM. S. Madsen, 2016: Do strong warm

ENSO events control the phase of the stratospheric QBO?

Geophys. Res. Lett., 43, 10 489–10 495, https://doi.org/10.1002/

2016GL070751.

Dai, A., 2013: The influence of the interdecadal Pacific oscillation

on US precipitation during 1923–2010. Climate Dyn., 41, 633–

646, https://doi.org/10.1007/s00382-012-1446-5.

——, and T.M. L.Wigley, 2000: Global patterns of ENSO-induced

precipitation.Geophys. Res. Lett., 27, 1283–1286, https://doi.org/

10.1029/1999GL011140.

Dee, D. P., and Coauthors, 2011: The ERA-Interim reanalysis:

Configuration and performance of the data assimilation sys-

tem.Quart. J. Roy. Meteor. Soc., 137, 553–597, https://doi.org/

10.1002/qj.828.

Deser, C., R. Guo, and F. Lehner, 2017: The relative contributions

of tropical Pacific sea surface temperatures and atmospheric

internal variability to the recent global warming hiatus.

Geophys. Res. Lett., 44, 7945–7954, https://doi.org/10.1002/

2017GL074273.

Domeisen, D. I. V., A. H. Butler, K. Fröhlich, M. Bittner, W. A.

Müller, and J. Baehr, 2015: Seasonal predictability over Eu-

rope arising from El Niño and stratospheric variability in the

MPI-ESM seasonal prediction system. J. Climate, 28, 256–271,

https://doi.org/10.1175/JCLI-D-14-00207.1.

Garfinkel, C. I., and D. L. Hartmann, 2010: Influence of the quasi-

biennial oscillation on the North Pacific and El Niño tele-

connections. J. Geophys. Res., 115, D20116, https://doi.org/

10.1029/2010JD014181.

Graf, H.-F., and D. Zanchettin, 2012: Central Pacific El Niño, the‘‘subtropical bridge,’’ and Eurasian climate. J. Geophys. Res.,

117, D01102, https://doi.org/10.1029/2011JD016493.

Greatbatch, R. J., J. Lu, and K. A. Peterson, 2004: Nonstationary

impact of ENSO on Euro-Atlantic winter climate. Geophys.

Res. Lett., 31, L02208, https://doi.org/10.1029/2003GL018542.

Halpert, M. S., and C. F. Ropelewski, 1992: Surface temperature

patterns associated with the Southern Oscillation. J. Climate,

5, 577–593, https://doi.org/10.1175/1520-0442(1992)005,0577:

STPAWT.2.0.CO;2.

Hamed, K. H., and A. R. Rao, 1998: A modified Mann-Kendall

trend test for autocorrelated data. J. Hydrol., 204, 182–196,

https://doi.org/10.1016/S0022-1694(97)00125-X.

Hoell, A., and C. Funk, 2013: The ENSO-related west Pacific sea

surface temperature gradient. J. Climate, 26, 9545–9562,

https://doi.org/10.1175/JCLI-D-12-00344.1.

——, M. Hoerling, J. Eischeid, K. Wolter, R. Dole, J. Perlwitz,

T. Xu, and L. Cheng, 2016: Does El Niño intensity matter for

California precipitation? Geophys. Res. Lett., 43, 819–825,

https://doi.org/10.1002/2015GL067102.

Hoerling, M. P., J. W. Hurrell, T. Xu, G. T. Bates, and

A. Phillips, 2004: Twentieth century North Atlantic climate

change. Part II: Understanding the effect of Indian Ocean

warming. Climate Dyn., 23, 391–405, https://doi.org/10.1007/

s00382-004-0433-x.

Horel, J. D., and J. M. Wallace, 1981: Planetary-scale atmo-

spheric phenomena associated with the Southern Oscilla-

tion. Mon. Wea. Rev., 109, 813–829, https://doi.org/10.1175/

1520-0493(1981)109,0813:PSAPAW.2.0.CO;2.

Huang, B., and Coauthors, 2015: Extended Reconstructed Sea

Surface Temperature version 4 (ERSST.v4). Part I: Upgrades

and intercomparisons. J. Climate, 28, 911–930, https://doi.org/

10.1175/JCLI-D-14-00006.1.

——, and Coauthors, 2016: Further exploring and quantifying un-

certainties for Extended Reconstructed Sea Surface Tem-

perature (ERSST) version 4 (v4). J. Climate, 29, 3119–3142,

https://doi.org/10.1175/JCLI-D-15-0430.1.

Hurrell, J. W., 1995: Decadal trends in the North Atlantic Oscil-

lation: Regional temperature and precipitation. Science, 269,

676–679, https://doi.org/10.1126/science.269.5224.676.

——, Y. Kushnir, G. Ottersen, and M. Visbeck, 2003: An overview

of the North Atlantic oscillation. The North Atlantic Oscilla-

tion: Climatic Significance and Environmental Impact, Geo-

phys.Monogr., Vol. 134, Amer. Geophys. Union, 1–35, https://

doi.org/10.1029/134GM01.

Hurwitz, M. M., N. Calvo, C. I. Garfinkel, A. H. Butler, S. Ineson,

C. Cagnazzo, E. Manzini, and C. Peña-Ortiz, 2014: Extra-

tropical atmospheric response to ENSO in the CMIP5

models. Climate Dyn., 43, 3367–3376, https://doi.org/10.1007/

s00382-014-2110-z.

Ineson, S., and A. A. Scaife, 2009: The role of the stratosphere

in the European climate response to El Niño. Nat. Geosci., 2,

32–36, https://doi.org/10.1038/ngeo381.

Jin, F. F., J. D. Neelin, and M. Ghil, 1994: El Niño on the devil’s

staircase: Annual subharmonic steps to chaos. Science, 264,

70–72, https://doi.org/10.1126/science.264.5155.70.

Jones, P. D., T. J. Osborn, and K. R. Briffa, 2003: Pressure-based

measures of the North Atlantic Oscillation (NAO): A com-

parison and an assessment of changes in the strength of the

NAO and in its influence on surface climate parameters. The

North Atlantic Oscillation: Climatic Significance and Envi-

ronmental Impact,Geophys. Monogr., Vol. 134, 51–62, https://

doi.org/10.1029/134GM03.

15 JANUARY 2019 ZHANG ET AL . 419

Kao, H. Y., and J. Y. Yu, 2009: Contrasting eastern-Pacific and

central-Pacific types of ENSO. J. Climate, 22, 615–632, https://

doi.org/10.1175/2008JCLI2309.1.

Kim, B.-H., and K.-J. Ha, 2015: Observed changes of global and

western Pacific precipitation associated with global warming

SST mode and mega-ENSO SST mode. Climate Dyn., 45,

3067–3075, https://doi.org/10.1007/s00382-015-2524-2.

Kug, J. S., F. F. Jin, and S. I. An, 2009: Two types of El Niño events:

Cold tongue El Niño and warm pool El Niño. J. Climate, 22,

1499–1515, https://doi.org/10.1175/2008JCLI2624.1.

Larkin, N. K., and D. E. Harrison, 2005: On the definition of

El Niño and associated seasonal average U.S. weather anom-

alies. Geophys. Res. Lett., 32, L13705, https://doi.org/10.1029/

2005GL022738.

Lau, K., and H. Weng, 2001: Coherent modes of global SST

and summer rainfall over China: An assessment of the

regional impacts of the 1997–98 El Niño. J. Climate, 14,

1294–1308, https://doi.org/10.1175/1520-0442(2001)014,1294:

CMOGSA.2.0.CO;2.

Lau, N. C., andM. J. Nath, 1990: A general circulationmodel study

of the atmospheric response to extratropical SST anomalies

observed in 1950–79. J. Climate, 3, 965–989, https://doi.org/

10.1175/1520-0442(1990)003,0965:AGCMSO.2.0.CO;2.

——, and ——, 1996: The role of the ‘‘atmospheric bridge’’ in

linking tropical Pacific ENSO events to extratropical SST

anomalies. J. Climate, 9, 2036–2057, https://doi.org/10.1175/

1520-0442(1996)009,2036:TROTBI.2.0.CO;2.

Levine, A. F., and M. J. McPhaden, 2016: How the July 2014

easterly wind burst gave the 2015–2016 El Niño a head start.

Geophys. Res. Lett., 43, 6503–6510, https://doi.org/10.1002/

2016GL069204.

L’Heureux, M. L., and Coauthors, 2017: Observing and predicting

the 2015/16 El Niño. Bull. Amer. Meteor. Soc., 98, 1363–1382,

https://doi.org/10.1175/BAMS-D-16-0009.1.

Li, Y., and N. C. Lau, 2012: Impact of ENSO in the atmospheric

variability over the North Atlantic in late winter—Role of

transient eddies. J. Climate, 25, 320–342, https://doi.org/

10.1175/JCLI-D-11-00037.1.

Lin, H., and Z. Wu, 2011: Contribution of the autumn Tibetan

Plateau snow cover to seasonal prediction of North American

winter temperature. J. Climate, 24, 2801–2813, https://doi.org/

10.1175/2010JCLI3889.1.

Liu, W., and Coauthors, 2015: Extended Reconstructed Sea Sur-

face Temperature version 4 (ERSST.v4). Part II: Parametric

and structural uncertainty estimations. J. Climate, 28, 931–951,

https://doi.org/10.1175/JCLI-D-14-00007.1.

Mariotti, A., 2007: How ENSO impacts precipitation in southwest

central Asia. Geophys. Res. Lett., 34, L16706, https://doi.org/

10.1029/2007GL030078.

Mathieu, P. P., R. T. Sutton, B. W. Dong, and M. Collins, 2004:

Predictability of winter climate over the North Atlantic

European region during ENSO events. J. Climate, 17,

1953–1974, https://doi.org/10.1175/1520-0442(2004)017,1953:

POWCOT.2.0.CO;2.

McPhaden, M. J., 1999: Genesis and evolution of the 1997-98

El Niño. Science, 283, 950–954, https://doi.org/10.1126/

science.283.5404.950.

Merkel, U., and M. Latif, 2002: A high resolution AGCM study

of the El Niño impact on the North Atlantic/European

sector.Geophys. Res. Lett., 29, 1291, https://doi.org/10.1029/

2001GL013726.

Mondal, A., S. Kundu, andA.Mukhopadhyay, 2012: Rainfall trend

analysis by Mann-Kendall test: A case study of north-eastern

part of Cuttack district, Orissa. Int. J. Geol. Earth Environ.

Sci., 2, 70–78.

Paek, H., J. Y. Yu, and C. Qian, 2017: Why were the 2015/2016 and

1997/1998 extreme El Niños different?Geophys. Res. Lett., 44,

1848–1856, https://doi.org/10.1002/2016GL071515.

Perlwitz, J., andH. F. Graf, 1995: The statistical connection between

tropospheric and stratospheric circulation of the Northern

Hemisphere in winter. J. Climate, 8, 2281–2295, https://doi.org/

10.1175/1520-0442(1995)008,2281:TSCBTA.2.0.CO;2.

Philander, S. G., and A. D. Seigel, 1985: Simulation of El Niño of

1982–1983.CoupledOcean–AtmosphereModels, J. C. J. Nihoul,

Ed., Elsevier Oceanography Series, Vol. 40, Elsevier, 517–541,

https://doi.org/10.1016/S0422-9894(08)70729-3.

Polvani, L. M., L. Sun, A. H. Butler, J. H. Richter, and C. Deser,

2017: Distinguishing stratospheric sudden warmings from

ENSO as key drivers of wintertime climate variability over the

North Atlantic and Eurasia. J. Climate, 30, 1959–1969, https://

doi.org/10.1175/JCLI-D-16-0277.1.

Rayner, N. A., D. E. Parker, E. B. Horton, C. K. Folland, L. V.

Alexander, D. P. Rowell, E. C. Kent, and A. Kaplan, 2003:

Global analyses of sea surface temperature, sea ice, and

night marine air temperatures since the late nineteenth

century. J. Geophys. Res., 108, 4407, https://doi.org/10.1029/

2002JD002670.

Richter, J. H., C. Deser, and L. Sun, 2015: Effects of stratospheric

variability on El Niño teleconnections. Environ. Res. Lett., 10,

124021, https://doi.org/10.1088/1748-9326/10/12/124021.

Robinson, W. A., 2000: Review of EWTS—The workshop on

extratropical SST anomalies. Bull. Amer. Meteor. Soc., 81,

567–577, https://doi.org/10.1175/1520-0477(2000)081,0567:

ROWTWO.2.3.CO;2.

Rodríguez-Fonseca, B., and Coauthors, 2016: A review of ENSO

influence on the North Atlantic. A non-stationary signal. At-

mosphere, 7, 87–105, https://doi.org/10.3390/atmos7070087.

Roeckner, E., and Coauthors, 2003: The atmospheric general cir-

culation model ECHAM5. Part I: Model description. Max

Planck Institute Rep. 349, 140 pp.

Ropelewski, C. F., and M. S. Halpert, 1987: Global and regional

scale precipitation patterns associated with the El Niño/Southern Oscillation.Mon. Wea. Rev., 115, 1606–1626, https://

doi.org/10.1175/1520-0493(1987)115,1606:GARSPP.2.0.CO;2.

——, and ——, 1996: Quantifying Southern Oscillation–precipitation

relationships. J. Climate, 9, 1043–1059, https://doi.org/10.1175/

1520-0442(1996)009,1043:QSOPR.2.0.CO;2.

Schreiber, R. W., and E. A. Schreiber, 1984: Central Pacific sea-

birds and the El Niño southern oscillation: 1982 to 1983

perspectives. Science, 225, 713–716, https://doi.org/10.1126/

science.225.4663.713.

Seager, R., Y. Kushnir, J. Nakamura, M. Ting, and N. Naik, 2010:

Northern Hemisphere winter snow anomalies: ENSO, NAO

and the winter of 2009/10. Geophys. Res. Lett., 37, L14703,

https://doi.org/10.1029/2010GL043830.

Shinoda, T., H. E. Hurlburt, and E. J. Metzger, 2011: Anom-

alous tropical ocean circulation associated with La NiñaModoki. J. Geophys. Res., 116, C12001, https://doi.org/10.1029/

2011JC007304.

Toniazzo, T., and A. A. Scaife, 2006: The influence of ENSO

on winter North Atlantic climate. Geophys. Res. Lett., 33,

L24704, https://doi.org/10.1029/2006GL027881.

Trenberth, K. E., and J. M. Caron, 2000: The Southern Oscillation

revisited: Sea level pressure, surface temperatures, and pre-

cipitation. J. Climate, 13, 4358–4365, https://doi.org/10.1175/

1520-0442(2000)013,4358:TSORSL.2.0.CO;2.

420 JOURNAL OF CL IMATE VOLUME 32

Uppala, S. M., and Coauthors, 2005: The ERA-40 re-analysis.Quart. J.

Roy.Meteor. Soc., 131, 2961–3012, https://doi.org/10.1256/qj.04.176.

Wallace, J. M., and D. S. Gutzler, 1981: Teleconnections in the

geopotential height field during the Northern Hemisphere

winter. Mon. Wea. Rev., 109, 784–812, https://doi.org/10.1175/

1520-0493(1981)109,0784:TITGHF.2.0.CO;2.

Wang, B., R. G. Wu, and X. H. Fu, 2000: Pacific–East Asia telecon-

nection: How does ENSO affect East Asian climate? J. Climate,

13, 1517–1536, https://doi.org/10.1175/1520-0442(2000)013,1517:

PEATHD.2.0.CO;2.

——, Z. Wu, J. Li, J. Liu, C. P. Chang, Y. H. Ding, and G. X. Wu,

2008: How to measure the strength of the East Asian summer

monsoon? J. Climate, 21, 4449–4463, https://doi.org/10.1175/

2008JCLI2183.1.

——, J. Liu, H. J. Kim, P. J. Webster, S. Y. Yim, and B. Q. Xiang,

2013: Northern Hemisphere summer monsoon intensified by

mega-El Niño/southern oscillation and Atlantic multidecadal

oscillation.Proc. Natl. Acad. Sci. USA, 110, 5347–5352, https://

doi.org/10.1073/pnas.1219405110.

Wang, C., and R. H. Weisberg, 2000: The 1997–98 El Niño evo-

lution relative to previous El Niño events. J. Climate, 13,

488–501, https://doi.org/10.1175/1520-0442(2000)013,0488:

TENOER.2.0.CO;2.

Weng, H., K. Ashok, S. K. Behera, A. S. Rao, and T. Yamagata,

2007: Impacts of recent El NiñoModoki on dry/wet conditions

in the Pacific rim during boreal summer. Climate Dyn., 29,113–129, https://doi.org/10.1007/s00382-007-0234-0.

Wolter, K., and M. S. Timlin, 1998: Measuring the strength of

ENSO events: How does 1997/98 rank?Weather, 53, 315–324,

https://doi.org/10.1002/j.1477-8696.1998.tb06408.x.

Wu, B., T. Li, and T. J. Zhou, 2010: Relative contributions of the

Indian Ocean and local SST anomalies to the maintenance of

the westernNorth Pacific anomalous anticyclone during the El

Niño decaying summer. J. Climate, 23, 2974–2986, https://doi.org/

10.1175/2010JCLI3300.1.

Wu, Z., and J. Li, 2009: Seasonal prediction of the global pre-

cipitation annual modes with the grid-point atmospheric model

of IAP LASG (GAMIL). Acta Meteor. Sin., 23, 428–437.

——, andH. Lin, 2012: Interdecadal variability of the ENSO-North

Atlantic Oscillation connection in boreal summer. Quart.

J. Roy. Meteor. Soc., 138, 1668–1675, https://doi.org/10.1002/

qj.1889.

——, and P. Zhang, 2015: Interdecadal variability of the mega-

ENSO–NAO synchronization in winter. Climate Dyn., 45,1117–1128, https://doi.org/10.1007/s00382-014-2361-8.

——, and L. Yu, 2016: Seasonal prediction of the East Asian

summer monsoon with a partial-least square model. Climate

Dyn., 46, 3067–3078, https://doi.org/10.1007/s00382-015-2753-4.

——, B. Wang, J. Li, and F. F. Jin, 2009: An emperical seasonal

prediction model of the East Asian summer monsoon using

ENSO and NAO. J. Geophys. Res., 114, D18120, https://

doi.org/10.1029/2009JD011733.

Zhang, L., Z. Wu, and Y. Zhou, 2016: Different impacts of typical

and atypical ENSO on the Indian summer rainfall: ENSO-

developing phase.Atmos.–Ocean, 54, 440–456, https://doi.org/10.1080/07055900.2016.1209156.

Zhang, P., Z. Wu, and H. Chen, 2017: Interdecadal variability

of the ENSO–North Pacific atmospheric circulation in

winter. Atmos.–Ocean, 55, 110–120, https://doi.org/10.1080/

07055900.2017.1291411.

Zhang, W. J., L. Wang, B. Q. Xiang, L. Qi, and J. H. He, 2015:

Impacts of two types of La Niña on the NAO during boreal

winter. Climate Dyn., 44, 1351–1366, https://doi.org/10.1007/

s00382-014-2155-z.

15 JANUARY 2019 ZHANG ET AL . 421